.This is a remote position and we are hiring candidates from the whole country.AgileEngine is one of the Inc. 5000 fastest-growing companies in the US and a top-3 ranked dev shop according to Clutch. We create award-winning custom software solutions that help companies across 15+ industries change the lives of millions.If you like a challenging environment where you're working with the best and are encouraged to learn and experiment every day, there's no better place - guaranteed! :)What you will doDesign a clear and lean data model that clearly outlines data sources and transformations over this data on top of DAGs and data orchestration tools like dagsters or airflow; Data validationand data model testing on each DAG step; Insights Layer Ownership: Build data models and algorithms to generate first-party data using statistical and machine learning techniques, including LLMs and natural language processing. Generate derived insights and determine accurate values from error-prone sources (e.G., headcount information); Data Product Development: Develop and enhance data products to improve the discoverability of meaningful knowledge and information in our database. Continuously improve similarity, relevance, normalization, and tagging algorithms that power our search engine; Pipeline Maintenance: Oversee data pipelines' maintenance and health to ensure accurate, efficient, and optimal data transformations by avoiding repetitive tasks or operations within the data; Team Collaboration: Collaborate with the team to devise product goals, outline milestones, and execute plans with minimal guidance; Data Warehouse Design: Contribute to the design of a robust data warehouse architecture by following best practices and industry standards. Transferring data from S3, loading data with different schedules and managing different data pipelines on top of a unique warehouse architecture, etc; Collaborate with our platform team to make design decisions on the optimal middle-layer database flow improving DAG execution times and costs.Must haves+4 years of experience as a Data Engineer; Programming Languages: Python, SQL; Orchestration Tools: Airflow, Dagster; Data Warehouses: Snowflake, Databricks; ETL Tools: DBT Models; Containerization: Docker; DevOps: AWS; Databases: Clickhouse, Postgres, DuckDB; Upper-intermediate English level.The benefits of joining usProfessional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands